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Abstract

In this chapter we synthesize the pedagogical agent literature published during 2005–2011. During these years, researchers have claimed that pedagogical agents serve a variety of educational purposes such as being adaptable and versatile; engendering realistic simulations; addressing learners’ sociocultural needs; fostering engagement, motivation, and responsibility; and improving learning and performance. Empirical results supporting these claims are mixed, and results are often contradictory. Our investigation of prior literature also reveals that current research focuses on the examination of cognitive issues through the use of experimental and quasi-experimental methods. Nevertheless, sociocultural investigations are becoming increasingly popular, while mixed methods approaches, and to a lesser extent interpretive research, are garnering some attention in the literature. Suggestions for future research include the deployment of agents in naturalistic contexts and open-ended environments, and investigation of agent outcomes and implications in long-term interventions.

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References

  • Adcock, A. B., Duggan, M. H., Nelson, E. K., & Nickel, C. (2006). Teaching effective helping skills at a distance. Quarterly Review of Distance Education, 7(4), 349–360.

    Google Scholar 

  • Adcock, A., & Van Eck, R. (2005). Reliability and factor structure of the attitude toward tutoring agent scale (ATTAS). Journal of Interactive Learning Research, 16(2), 195–212.

    Google Scholar 

  • Angeli, A. D., & Brahnam, S. (2008). I hate you! Disinhibition with virtual partners. Interacting with Computers, 20(3), 302–310.

    Article  Google Scholar 

  • Baddeley, A. D. (1992). Working memory. Science, 255, 556–559.

    Article  Google Scholar 

  • Bandura, A. (1986). Social foundations of thought and action: A social-cognitive theory. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Baylor, A. L. (1999). Intelligent agents as cognitive tools. Educational Technology, 39(2), 36–40.

    Google Scholar 

  • Baylor, A. L. (2009). Promoting motivation with virtual agents and avatars: Role of visual presence and appearance. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 364(1535), 3559–3565.

    Article  Google Scholar 

  • Baylor, A. L. (2011). The design of motivational agents and avatars. Educational Technology Research and Development, 59(2), 291–300.

    Article  Google Scholar 

  • Baylor, A., & Kim, Y. (2005). Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence in Education, 15(1), 95–115.

    Google Scholar 

  • Baylor, A. L., & Kim, S. (2009). Designing nonverbal communication for pedagogical agents: When less is more. Computers in Human Behavior, 25(2), 450–457.

    Article  Google Scholar 

  • Baylor, A. L., & Ryu, J. (2003). Does the presence of image and animation enhance pedagogical agent persona? Journal of Educational Computing Research, 28, 373–395.

    Article  Google Scholar 

  • Bickmore, T. (2003). Relational agents: Effecting change through human-computer relationships. Unpublished PhD Thesis, Massachusetts Institute of Technology.

    Google Scholar 

  • Bickmore, T., Shulman, D., & Yin, L. (2009). Engagement vs. deceit: Virtual humans with human autobiographies. Intelligent Virtual Agents: Lecture Notes in Computer Science, 5773, 6–19.

    Article  Google Scholar 

  • Biswas, G., Leelawong, K., Schwartz, D., Vye, N., & The Teachable Agents Group at Vanderbilt. (2005). Learning by teaching: A new agent paradigm for educational software. Applied Artificial Intelligence, 19, 363–392.

    Article  Google Scholar 

  • Chase, C., Chin, D., Oppezzo, M., & Schwartz, D. (2009). Teachable agents and the protĂ©gĂ© effect: Increasing the effort towards learning. Journal of Science Education and Technology, 18, 334–352.

    Article  Google Scholar 

  • Choi, S., & Clark, R. (2006). Cognitive and affective benefits of an animated pedagogical agent for learning English as a second language. Journal of Educational Computing Research, 34(4), 441–466.

    Article  Google Scholar 

  • Chou, C., Chan, T., & Lin, C. (2003). Redefining the learning companion: The past, present, and future of educational agents. Computers in Education, 40(3), 255–269.

    Article  Google Scholar 

  • Clarebout, G., & Elen, J. (2006). Open learning environments and the impact of a pedagogical agent. Journal of Educational Computing Research, 35(3), 211–226.

    Article  Google Scholar 

  • Clarebout, G., & Elen, J. (2007). In search of pedagogical agents’ modality and dialogue effects in open learning environments. Journal of Instructional Science and Technology, 10(1), 1–15.

    Google Scholar 

  • *Clark, R. E., & Choi, S. (2005). Five design principles for experiments on the effects of animated pedagogical agents. Journal of Educational Computing Research, 32(3), 209–225.

    Google Scholar 

  • D’Mello, S. K., Craig, S. D., Witherspoon, A., McDaniel, B., & Graesser, A. C. (2008). Automatic detection of learner’s affect from conversational cues. User Modeling and User-Adapted Interaction, 18(1–2), 45–80.

    Article  Google Scholar 

  • D’Mello, S., & Graesser, A. C. (2010). Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features. User Modeling and User-adapted Interaction, 20(2), 147–187.

    Article  Google Scholar 

  • Dehn, D., & van Mulken, S. (2000). The impact of animated interface agents: A review of empirical research. International Journal of Human Computer Studies, 52(1), 1–22.

    Article  Google Scholar 

  • Dirkin, K. H., Mishra, P., & Altermatt, E. (2005). All or nothing: Levels of sociability of a pedagogical software agent and its impact on student perceptions and learning. Journal of Educational Multimedia and Hypermedia, 14(2), 113–127.

    Google Scholar 

  • Doering, A., Veletsianos, G., & Yerasimou, T. (2008). Conversational agents and their longitudinal affordances on communication and interaction. Journal of Interactive Learning Research, 19(2), 251–270.

    Google Scholar 

  • *Domagk, S. (2010). Do pedagogical agents facilitate learner motivation and learning outcomes? Journal of Media Psychology: Theories, Methods, and Applications, 22(2), 84–97.

    Google Scholar 

  • Dunsworth, Q., & Atkinson, R. (2007). Fostering multimedia learning of science: Exploring the role of an animated agent’s image. Computers in Education, 49(3), 677–690.

    Article  Google Scholar 

  • Frechette, C., & Moreno, R. (2010). The roles of animated pedagogical agents’ presence and nonverbal communication in multimedia learning environments. Media Psychology, 22(2), 61–72.

    Article  Google Scholar 

  • Gilbert, J., Wilson, D., & Gupta, P. (2005). Learning C with Adam. International Journal on E-Learning, 4(3), 337–350.

    Google Scholar 

  • *Graesser, A. C., Chipman, P., Haynes, B. C., & Olney, A. (2005). AutoTutor: An intelligent tutoring system with mixed-initiative dialogue. IEEE Transactions in Education, 48, 612–618.

    Google Scholar 

  • Graesser, A. C., Jackson, G. T., & McDaniel, B. (2007). AutoTutor holds conversations with learners that are responsive to their cognitive and emotional states. Educational Technology, 47, 19–22.

    Google Scholar 

  • Graesser, A., Jeon, M., & Dufty, D. (2008). Agent technologies designed to facilitate interactive knowledge construction. Discourse Processes, 45, 298–322.

    Article  Google Scholar 

  • Graesser, A., & McNamara, D. (2010). Self-regulated learning in learning environments with pedagogical agents that interact in natural language. Educational Psychologist, 45(4), 234–244.

    Article  Google Scholar 

  • *Gulz, A. (2004). Benefits of virtual characters in computer based learning environments: Claims and evidence. International Journal of Artificial Intelligence in Education, 14, 313–334.

    Google Scholar 

  • Gulz, A. (2005). Social enrichment by virtual characters—Differential benefits. Journal of Computer Assisted Learning, 21, 405–418.

    Article  Google Scholar 

  • Gulz, A., & Haake, M. (2006). Design of animated pedagogical agents—A look at their look. International Journal of Human Computer Studies, 64(4), 322–339.

    Article  Google Scholar 

  • Gulz, A., & Haake, M. (2010). Challenging gender stereotypes using virtual pedagogical characters. In S. Goodman, S. Booth, & G. Kirkup (Eds.), Gender issues in learning and working with Information Technology: Social constructs and cultural contexts. Hershey, PA: IGI Global.

    Google Scholar 

  • Haake, M., & Gulz, A. (2008). Visual stereotypes and virtual pedagogical agents. Educational Technology & Society, 11(4), 1–15.

    Google Scholar 

  • Hawryskiewycz, I. (2006). Software agents for managing learning plans. Issues in Informing Science and Information Technology, 3, 269–277.

    Google Scholar 

  • Hubal, R. C., Fishbein, D. H., Sheppard, M. S., Paschall, M. J., Eldreth, D. L., & Hyde, C. T. (2008). How do varied populations interact with embodied conversational agents? Findings from inner-city adolescents and prisoners. Computers in Human Behavior, 24(3), 1104–1138.

    Article  Google Scholar 

  • Jackson, G. T., & Graesser, A. C. (2007). Content matters: An investigation of feedback categories within an ITS. In R. Luckin, K. Koedinger, & J. Greer (Eds.), Artificial intelligence in education: Building technology rich learning contexts that work. Amsterdam: IOS Press.

    Google Scholar 

  • Kester, L., Lehnen, C., Van Gerven, P., & Kirschner, P. (2006). Just-in-time, schematic supportive information presentation during cognitive skill acquisition. Computers in Human Behavior, 22(1), 93–112.

    Article  Google Scholar 

  • *Kim, Y., & Baylor, A. (2006). A socio-cognitive framework for pedagogical agents as learning companions. Educational Technology Research and Development, 54(6), 569–596.

    Google Scholar 

  • Kim, C., & Baylor, A. (2008). A virtual change agent: Motivating pre-service teachers to integrate technology in their future classrooms. Educational Technology & Society, 11(2), 309–321.

    Google Scholar 

  • Kim, Y., Baylor, A., & PALS Group. (2006). Pedagogical agents as learning companions: The role of agent competency and type of interaction. Educational Technology Research and Development, 54(3), 223–243.

    Article  Google Scholar 

  • Kim, Y., Baylor, A. L., & Shen, E. (2007). Pedagogical agents as learning companions: The impact of agent emotion and gender. Journal of Computer Assisted Learning, 23(3), 220–234.

    Article  Google Scholar 

  • Kim, Y., & Wei, Q. (2011). The impact of learner attributes and learner choice in an agent-based environment. Computers in Education, 56, 505–514.

    Article  Google Scholar 

  • Kramer, N. C., & Bente, G. (2010). Personalizing e-learning: The social effects of pedagogical agents. Educational Psychology Review, 22, 71–87.

    Article  Google Scholar 

  • Lin, Y., Chen, M., Wu, T., & Yeh, Y. (2008). The effectiveness of a pedagogical agent-based learning system for teaching word recognition to children with moderate mental retardation. British Journal of Educational Technology, 39(4), 715–720.

    Article  Google Scholar 

  • Lindström, P., Gulz, A., Haake, M., & SjödĂ©n, B. (2011). Matching and mismatching between the pedagogical design principles of a math game and the actual practices of play. Journal of Computer Assisted Learning, 27(1), 90–102.

    Article  Google Scholar 

  • Louwerse, M. M., Graesser, A. C., Lu, S., & Mitchell, H. H. (2005). Social cues in animated conversational agents. Applied Cognitive Psychology, 19(6), 693–704.

    Article  Google Scholar 

  • Louwerse, M., Graesser, A., Namara, D., & Lu, S. (2009). Embodied conversational agents as conversational partners. Applied Cognitive Psychology, 23(9), 1244–1255.

    Article  Google Scholar 

  • Lusk, M., & Atkinson, R. (2007). Animated pedagogical agents: Does their degree of embodiment impact learning from static or animated worked examples? Applied Cognitive Psychology, 21, 747–764.

    Article  Google Scholar 

  • Mahmood, K., & Ferneley, E. (2006). Embodied agents in e-learning environments: An exploratory case study. Journal of Interactive Learning Research, 17(2), 143–162.

    Google Scholar 

  • *Moreno, R. (2004). Animated pedagogical agents in educational technology. Educational Technology, 44(6), 23–30.

    Google Scholar 

  • Moreno, R., & Flowerday, T. (2006). Students’ choice of animated pedagogical agents in science learning: A test of the similarity-attraction hypothesis on gender and ethnicity. Contemporary Educational Psychology, 31(2), 186–207.

    Article  Google Scholar 

  • *Moreno, R., Mayer, R. E., Spires, H., & Lester, J. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19, 177–213.

    Google Scholar 

  • Murray, M., & Tenenbaum, G. (2010). Computerized pedagogical agents as an educational means for developing physical self-efficacy and encouraging activity in youth. Journal of Educational Computing Research, 42(3), 267–283.

    Article  Google Scholar 

  • Nass, C., & Brave, S. (2005). Wired for speech: How voice activates and advances the human-computer relationship. Cambridge, MA: MIT Press.

    Google Scholar 

  • Norman, D. (1997). How might people interact with agents. In J. M. Bradshaw (Ed.), Software agents (pp. 49–56). Menlo Park, CA: MIT Press.

    Google Scholar 

  • Payr, S. (2003). The virtual university’s faculty: An overview of educational agents. Applied Artificial Intelligence, 17(1), 1–19.

    Article  Google Scholar 

  • *Reeves, B., & Nass, C. (1996). The media equation: How people treat computers, television, and new media like real people and places. New York, NY: Cambridge University Press

    Google Scholar 

  • Rosenberg-Kima, R., Baylor, A., Plant, E., & Doerr, C. (2008). Interface agents as social models for female students: The effects of agent visual presence and appearance on female students’ attitudes and beliefs. Computers in Human Behavior, 24(6), 2741–2756.

    Article  Google Scholar 

  • Rosenberg-Kima, R., Plant, E., Doerr, C., & Baylor, A. (2010). The influence of computer-based model’s race and gender on female students’ attitudes and beliefs towards engineering. Journal of Engineering Education, 99, 35–44.

    Article  Google Scholar 

  • Schwartz, D. L., Blair, K. P., Biswas, G., Leelawong, K., & Davis, J. (2007). Animations of thought: Interactivity in the teachable agent paradigm. In R. Lowe & W. Schnotz (Eds.), Learning with animation: Research and implications for design (pp. 114–140). UK: Cambridge University Press.

    Google Scholar 

  • Sklar, E., & Richards, D. (2010). Agent-based systems for human learners. The Knowledge Engineering Review, 25(2), 111–135.

    Article  Google Scholar 

  • Sträfling, N., Fleischer, I., Polzer, C., Leutner, D., & Krämer, N. C. (2010). Teaching learning strategies with a pedagogical agent. Journal of Media Psychology: Theories, Methods, and Applications, 22(2), 73–83.

    Article  Google Scholar 

  • Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312.

    Article  Google Scholar 

  • Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32, 9–31.

    Article  Google Scholar 

  • van MerriĂ«nboer, J., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 55(3), 5–13.

    Article  Google Scholar 

  • Veletsianos, G. (2007). Cognitive and affective benefits of an animated pedagogical agent: Considering contextual relevance and aesthetics. Journal of Educational Computing Research, 36(4), 373–377.

    Article  Google Scholar 

  • Veletsianos, G. (2009). The impact and implications of virtual character expressiveness on learning and agent-learner interactions. Journal of Computer Assisted Learning, 25(4), 345–357.

    Article  Google Scholar 

  • Veletsianos, G. (2010). Contextually relevant pedagogical agents: Visual appearance, stereotypes, and first impressions and their impact on learning. Computers in Education, 55(2), 576–585.

    Article  Google Scholar 

  • Veletsianos, G. (2012). How do Learners Respond to Pedagogical Agents that Deliver Social-oriented Non-task Messages? Impact on Student Learning, Perceptions, and Experiences. Computers in Human Behavior, 28(1), 275–283.

    Article  Google Scholar 

  • Veletsianos, G., Heller, R., Overmyer, S., & Procter, M. (2010). Conversational agents in virtual worlds: Bridging disciplines. British Journal of Educational Technology, 41(1), 123–140.

    Article  Google Scholar 

  • *Veletsianos, G., & Miller, C. (2008). Conversing with pedagogical agents: A phenomenological exploration of interacting with digital entities. British Journal of Educational Technology, 39(6), 969–986.

    Google Scholar 

  • Veletsianos, G., Miller, C., & Doering, A. (2009). EnALI: A research and design framework for virtual characters and pedagogical agents. Journal of Educational Computing Research, 41(2), 171–194.

    Article  Google Scholar 

  • Veletsianos, G., Scharber, C., & Doering, A. (2008). When sex, drugs, and violence enter the classroom: Conversations between adolescent social studies students and a female pedagogical agent. Interacting with Computers, 20(3), 292–301.

    Article  Google Scholar 

  • Wagster, J., Tan, J., Wu, Y., Biswas, G., & Schwartz, D. L. (2007). Do learning by teaching environments with metacognitive support help students develop better learning behaviors? In D. S. McNamara & J. G. Trafton (Eds.), Proceeding of the 29th Meeting of the Cognitive Science Society (pp. 695–700). Nashville, TN: Cognitive Science Society.

    Google Scholar 

  • Wilson, C., Sudol, L. A., Stephenson, C., & Stehlik, M. (2010). Running on empty: The Failure to teach K-12 computer science in the digital age. Association for Computing Machinery and The Computer Science Teachers Association. Retrieved December 10, 2011, from http://www.acm.org/runningonempty/fullreport.pdf

  • Woo, H. L. (2008). Designing multimedia learning environments using animated pedagogical agents: Factors and issues. Journal of Computer Assisted Learning, 25, 203–218.

    Article  Google Scholar 

  • Yung, H. I., & Dwyer, F. M. (2010). Effects of an animated agent with instructional strategies in facilitating student achievement of educational objectives in multimedia learning. International Journal of Instructional Media, 37(1), 55–64.

    Google Scholar 

  • Zumbach, J., Schmitt, S., Reimann, P., & Starkloff, P. (2006). Learning life sciences: Design and development of a virtual molecular biology learning lab. Journal of Computers in Mathematics and Science Teaching, 25(3), 281–300.

    Google Scholar 

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Correspondence to George Veletsianos Ph.D. .

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Veletsianos, G., Russell, G.S. (2014). Pedagogical Agents. In: Spector, J., Merrill, M., Elen, J., Bishop, M. (eds) Handbook of Research on Educational Communications and Technology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3185-5_61

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